Abstract
Synchronisation and coordination are omnipresent and essential in humans interactions. Because of their unavoidable and unintentional aspect, those phenomena could be the consequences of a low level mechanism: a driving force originating from external stimuli called the entrainment effect. In the light of its importance in interaction and wishing to define new HRI, we suggest to model this entrainment to highlight its efficiency for gesture learning during imitative games and for reducing the computational complexity. We will put forward the capacity of adaptation offered by the entrainment effect. Hence, we present in this paper a neural model for gesture learning by imitation using entrainment effect applied to a NAO robot interacting with a human partner.
This work is funded by the DGA and the DIRAC project.
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Ansermin, E., Mostafaoui, G., Beaussé, N., Gaussier, P. (2016). Learning to Synchronously Imitate Gestures Using Entrainment Effect. In: Tuci, E., Giagkos, A., Wilson, M., Hallam, J. (eds) From Animals to Animats 14. SAB 2016. Lecture Notes in Computer Science(), vol 9825. Springer, Cham. https://doi.org/10.1007/978-3-319-43488-9_20
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DOI: https://doi.org/10.1007/978-3-319-43488-9_20
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